R9212/driver.m
5fffa754af2cmaster

driver.m
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			function driver(input_directory, output_directory)
			% Find files.
			files = {};
			for f = dir(input_directory)'
			if exist(fullfile(input_directory, f.name), 'file') == 2 && f.name(1) ~= '.' && all(f.name(end - 2 : end) == 'psv')
			files{end + 1} = f.name;
			end
			end

			if ~exist(output_directory, 'dir')
			mkdir(output_directory)
			end

			% Load model.
			model = load_sepsis_model();

			% Iterate over files.
			num_files = length(files);
			for i = 1:num_files
			% Load data.
			input_file = fullfile(input_directory, files{i});
			data = load_challenge_data(input_file);

			% Make predictions.
			num_rows = size(data, 1);
			scores = zeros(num_rows, 1);
			labels = zeros(num_rows, 1);
			for t = 1:num_rows
			current_data = data(1:t, :);
			[current_score, current_label] = get_sepsis_score(current_data, model);
			scores(t) = current_score;
			labels(t) = current_label;
			end

			% Save results.
			output_file = fullfile(output_directory, files{i});
			save_challenge_predictions(output_file, scores, labels);
			end
			end

			function data = load_challenge_data(file)
			f = fopen(file, 'rt');
			try
			l = fgetl(f);
			column_names = strsplit(l, '\|');
			data = dlmread(file, '\|', 1, 0);
			catch ex
			fclose(f);
			rethrow(ex);
			end
			fclose(f);

			% Ignore SepsisLabel column if present.
			if strcmp(column_names(end), 'SepsisLabel')
			column_names = column_names(1 : end-1);
			data = data(:, 1 : end-1);
			end
			end

			function save_challenge_predictions(file, scores, labels)
			fid = fopen(file, 'wt');
			fprintf(fid, 'PredictedProbability\|PredictedLabel\n');
			fclose(fid);
			dlmwrite(file, [scores labels], 'delimiter', '\|', '-append');
			end